Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
values |
|---|---|---|---|---|
20,902 | Imagining Probabilistic Belief Change as Imaging (Technical Report) | cs.AI | Imaging is a form of probabilistic belief change which could be employed for
both revision and update. In this paper, we propose a new framework for
probabilistic belief change based on imaging, called Expected Distance Imaging
(EDI). EDI is sufficiently general to define Bayesian conditioning and other
forms of imagin... | computer science |
20,903 | Answer Set Programming for Non-Stationary Markov Decision Processes | cs.AI | Non-stationary domains, where unforeseen changes happen, present a challenge
for agents to find an optimal policy for a sequential decision making problem.
This work investigates a solution to this problem that combines Markov Decision
Processes (MDP) and Reinforcement Learning (RL) with Answer Set Programming
(ASP) in... | computer science |
20,904 | Tramp Ship Scheduling Problem with Berth Allocation Considerations and
Time-dependent Constraints | cs.AI | This work presents a model for the Tramp Ship Scheduling problem including
berth allocation considerations, motivated by a real case of a shipping
company. The aim is to determine the travel schedule for each vessel
considering multiple docking and multiple time windows at the berths. This work
is innovative due to the... | computer science |
20,905 | A Reasoning System for a First-Order Logic of Limited Belief | cs.AI | Logics of limited belief aim at enabling computationally feasible reasoning
in highly expressive representation languages. These languages are often
dialects of first-order logic with a weaker form of logical entailment that
keeps reasoning decidable or even tractable. While a number of such logics have
been proposed i... | computer science |
20,906 | Distributed Online Learning of Event Definitions | cs.AI | Logic-based event recognition systems infer occurrences of events in time
using a set of event definitions in the form of first-order rules. The Event
Calculus is a temporal logic that has been used as a basis in event recognition
applications, providing among others, direct connections to machine learning,
via Inducti... | computer science |
20,907 | PANFIS++: A Generalized Approach to Evolving Learning | cs.AI | The concept of evolving intelligent system (EIS) provides an effective avenue
for data stream mining because it is capable of coping with two prominent
issues: online learning and rapidly changing environments. We note at least
three uncharted territories of existing EISs: data uncertainty, temporal system
dynamic, red... | computer science |
20,908 | Metacognitive Learning Approach for Online Tool Condition Monitoring | cs.AI | As manufacturing processes become increasingly automated, so should tool
condition monitoring (TCM) as it is impractical to have human workers monitor
the state of the tools continuously. Tool condition is crucial to ensure the
good quality of products: Worn tools affect not only the surface quality but
also the dimens... | computer science |
20,909 | A New Medical Diagnosis Method Based on Z-Numbers | cs.AI | How to handle uncertainty in medical diagnosis is an open issue. In this
paper, a new decision making methodology based on Z-numbers is presented.
Firstly, the experts' opinions are represented by Z-numbers. Z-number is an
ordered pair of fuzzy numbers denoted as Z = (A, B). Then, a new method for
ranking fuzzy numbers... | computer science |
20,910 | An Anthropic Argument against the Future Existence of Superintelligent
Artificial Intelligence | cs.AI | This paper uses anthropic reasoning to argue for a reduced likelihood that
superintelligent AI will come into existence in the future. To make this
argument, a new principle is introduced: the Super-Strong Self-Sampling
Assumption (SSSSA), building on the Self-Sampling Assumption (SSA) and the
Strong Self-Sampling Assu... | computer science |
20,911 | Evidence for the size principle in semantic and perceptual domains | cs.AI | Shepard's Universal Law of Generalization offered a compelling case for the
first physics-like law in cognitive science that should hold for all
intelligent agents in the universe. Shepard's account is based on a rational
Bayesian model of generalization, providing an answer to the question of why
such a law should eme... | computer science |
20,912 | Composition of Credal Sets via Polyhedral Geometry | cs.AI | Recently introduced composition operator for credal sets is an analogy of
such operators in probability, possibility, evidence and valuation-based
systems theories. It was designed to construct multidimensional models (in the
framework of credal sets) from a system of low- dimensional credal sets. In
this paper we stud... | computer science |
20,913 | A note on the uniqueness of models in social abstract argumentation | cs.AI | Social abstract argumentation is a principled way to assign values to
conflicting (weighted) arguments. In this note we discuss the important
property of the uniqueness of the model. | computer science |
20,914 | Solving Multi-Objective MDP with Lexicographic Preference: An
application to stochastic planning with multiple quantile objective | cs.AI | In most common settings of Markov Decision Process (MDP), an agent evaluate a
policy based on expectation of (discounted) sum of rewards. However in many
applications this criterion might not be suitable from two perspective: first,
in risk aversion situation expectation of accumulated rewards is not robust
enough, thi... | computer science |
20,915 | Memetic search for identifying critical nodes in sparse graphs | cs.AI | Critical node problems involve identifying a subset of critical nodes from an
undirected graph whose removal results in optimizing a pre-defined measure over
the residual graph. As useful models for a variety of practical applications,
these problems are computational challenging. In this paper, we study the
classic cr... | computer science |
20,916 | A rational analysis of curiosity | cs.AI | We present a rational analysis of curiosity, proposing that people's
curiosity is driven by seeking stimuli that maximize their ability to make
appropriate responses in the future. This perspective offers a way to unify
previous theories of curiosity into a single framework. Experimental results
confirm our model's pre... | computer science |
20,917 | A Survey of Question Answering for Math and Science Problem | cs.AI | Turing test was long considered the measure for artificial intelligence. But
with the advances in AI, it has proved to be insufficient measure. We can now
aim to mea- sure machine intelligence like we measure human intelligence. One
of the widely accepted measure of intelligence is standardized math and science
test. I... | computer science |
20,918 | Clingcon: The Next Generation | cs.AI | We present the third generation of the constraint answer set system clingcon,
combining Answer Set Programming (ASP) with finite domain constraint processing
(CP). While its predecessors rely on a black-box approach to hybrid solving by
integrating the CP solver gecode, the new clingcon system pursues a lazy
approach u... | computer science |
20,919 | A Formal Characterization of the Local Search Topology of the Gap
Heuristic | cs.AI | The pancake puzzle is a classic optimization problem that has become a
standard benchmark for heuristic search algorithms. In this paper, we provide
full proofs regarding the local search topology of the gap heuristic for the
pancake puzzle. First, we show that in any non-goal state in which there is no
move that will ... | computer science |
20,920 | Progression of Decomposed Local-Effect Action Theories | cs.AI | In many tasks related to reasoning about consequences of a logical theory, it
is desirable to decompose the theory into a number of weakly-related or
independent components. However, a theory may represent knowledge that is
subject to change, as a result of executing actions that have effects on some
of the initial pro... | computer science |
20,921 | On the Complexity of Semantic Integration of OWL Ontologies | cs.AI | We propose a new mechanism for integration of OWL ontologies using semantic
import relations. In contrast to the standard OWL importing, we do not require
all axioms of the imported ontologies to be taken into account for reasoning
tasks, but only their logical implications over a chosen signature. This
property comes ... | computer science |
20,922 | Awareness improves problem-solving performance | cs.AI | The brain's self-monitoring of activities, including internal activities -- a
functionality that we refer to as awareness -- has been suggested as a key
element of consciousness. Here we investigate whether the presence of an
inner-eye-like process (monitor) that supervises the activities of a number of
subsystems (ope... | computer science |
20,923 | Quantifying Aspect Bias in Ordinal Ratings using a Bayesian Approach | cs.AI | User opinions expressed in the form of ratings can influence an individual's
view of an item. However, the true quality of an item is often obfuscated by
user biases, and it is not obvious from the observed ratings the importance
different users place on different aspects of an item. We propose a
probabilistic modeling... | computer science |
20,924 | Exploiting the Pruning Power of Strong Local Consistencies Through
Parallelization | cs.AI | Local consistencies stronger than arc consistency have received a lot of
attention since the early days of CSP research. %because of the strong pruning
they can achieve. However, they have not been widely adopted by CSP solvers.
This is because applying such consistencies can sometimes result in
considerably smaller se... | computer science |
20,925 | Constrained Bayesian Networks: Theory, Optimization, and Applications | cs.AI | We develop the theory and practice of an approach to modelling and
probabilistic inference in causal networks that is suitable when
application-specific or analysis-specific constraints should inform such
inference or when little or no data for the learning of causal network
structure or probability values at nodes are... | computer science |
20,926 | A Method for Determining Weights of Criterias and Alternative of Fuzzy
Group Decision Making Problem | cs.AI | In this paper, we constructed a model to determine weights of criterias and
presented a solution for determining the optimal alternative by using the
constructed model and relationship analysis between criterias in fuzzy group
decision-making problem with different forms of preference information of
decision makers on ... | computer science |
20,927 | New Reinforcement Learning Using a Chaotic Neural Network for Emergence
of "Thinking" - "Exploration" Grows into "Thinking" through Learning - | cs.AI | Expectation for the emergence of higher functions is getting larger in the
framework of end-to-end reinforcement learning using a recurrent neural
network. However, the emergence of "thinking" that is a typical higher function
is difficult to realize because "thinking" needs non fixed-point, flow-type
attractors with b... | computer science |
20,928 | Text-based Adventures of the Golovin AI Agent | cs.AI | The domain of text-based adventure games has been recently established as a
new challenge of creating the agent that is both able to understand natural
language, and acts intelligently in text-described environments.
In this paper, we present our approach to tackle the problem. Our agent,
named Golovin, takes advanta... | computer science |
20,929 | All-relevant feature selection using multidimensional filters with
exhaustive search | cs.AI | This paper describes a method for identification of the informative variables
in the information system with discrete decision variables. It is targeted
specifically towards discovery of the variables that are non-informative when
considered alone, but are informative when the synergistic interactions between
multiple ... | computer science |
20,930 | Multiobjective Programming for Type-2 Hierarchical Fuzzy Inference Trees | cs.AI | This paper proposes a design of hierarchical fuzzy inference tree (HFIT). An
HFIT produces an optimum treelike structure, i.e., a natural hierarchical
structure that accommodates simplicity by combining several low-dimensional
fuzzy inference systems (FISs). Such a natural hierarchical structure provides
a high degree ... | computer science |
20,931 | AI, Native Supercomputing and The Revival of Moore's Law | cs.AI | Based on Alan Turing's proposition on AI and computing machinery, which
shaped Computing as we know it today, the new AI computing machinery should
comprise a universal computer and a universal learning machine. The later
should understand linear algebra natively to overcome the slowdown of Moore's
law. In such a unive... | computer science |
20,932 | REMIX: Automated Exploration for Interactive Outlier Detection | cs.AI | Outlier detection is the identification of points in a dataset that do not
conform to the norm. Outlier detection is highly sensitive to the choice of the
detection algorithm and the feature subspace used by the algorithm. Extracting
domain-relevant insights from outliers needs systematic exploration of these
choices s... | computer science |
20,933 | Identification and Off-Policy Learning of Multiple Objectives Using
Adaptive Clustering | cs.AI | In this work, we present a methodology that enables an agent to make
efficient use of its exploratory actions by autonomously identifying possible
objectives in its environment and learning them in parallel. The identification
of objectives is achieved using an online and unsupervised adaptive clustering
algorithm. The... | computer science |
20,934 | Induction of Interpretable Possibilistic Logic Theories from Relational
Data | cs.AI | The field of Statistical Relational Learning (SRL) is concerned with learning
probabilistic models from relational data. Learned SRL models are typically
represented using some kind of weighted logical formulas, which make them
considerably more interpretable than those obtained by e.g. neural networks. In
practice, ho... | computer science |
20,935 | The Bag Semantics of Ontology-Based Data Access | cs.AI | Ontology-based data access (OBDA) is a popular approach for integrating and
querying multiple data sources by means of a shared ontology. The ontology is
linked to the sources using mappings, which assign views over the data to
ontology predicates. Motivated by the need for OBDA systems supporting
database-style aggreg... | computer science |
20,936 | Model-Based Planning in Discrete Action Spaces | cs.AI | Planning actions using learned and differentiable forward models of the world
is a general approach which has a number of desirable properties, including
improved sample complexity over model-free RL methods, reuse of learned models
across different tasks, and the ability to perform efficient gradient-based
optimizatio... | computer science |
20,937 | Combining tabu search and graph reduction to solve the maximum balanced
biclique problem | cs.AI | The Maximum Balanced Biclique Problem is a well-known graph model with
relevant applications in diverse domains. This paper introduces a novel
algorithm, which combines an effective constraint-based tabu search procedure
and two dedicated graph reduction techniques. We verify the effectiveness of
the algorithm on 30 cl... | computer science |
20,938 | Generalizing the Role of Determinization in Probabilistic Planning | cs.AI | The stochastic shortest path problem (SSP) is a highly expressive model for
probabilistic planning. The computational hardness of SSPs has sparked interest
in determinization-based planners that can quickly solve large problems.
However, existing methods employ a simplistic approach to determinization. In
particular, t... | computer science |
20,939 | Sketched Answer Set Programming | cs.AI | Answer Set Programming (ASP) is a powerful modeling formalism for
combinatorial problems. However, writing ASP models is not trivial. We propose
a novel method, called Sketched Answer Set Programming (SkASP), aiming at
supporting the user in resolving this issue. The user writes an ASP program
while marking uncertain p... | computer science |
20,940 | Experience enrichment based task independent reward model | cs.AI | For most reinforcement learning approaches, the learning is performed by
maximizing an accumulative reward that is expectedly and manually defined for
specific tasks. However, in real world, rewards are emergent phenomena from the
complex interactions between agents and environments. In this paper, we propose
an implic... | computer science |
20,941 | AIXIjs: A Software Demo for General Reinforcement Learning | cs.AI | Reinforcement learning is a general and powerful framework with which to
study and implement artificial intelligence. Recent advances in deep learning
have enabled RL algorithms to achieve impressive performance in restricted
domains such as playing Atari video games (Mnih et al., 2015) and, recently,
the board game Go... | computer science |
20,942 | Compatible extensions and consistent closures: a fuzzy approach | cs.AI | In this paper $\ast$--compatible extensions of fuzzy relations are studied,
generalizing some results obtained by Duggan in case of crisp relations. From
this general result are obtained as particular cases fuzzy versions of some
important extension theorems for crisp relations (Szpilrajn, Hansson,
Suzumura). Two notio... | computer science |
20,943 | Living Together: Mind and Machine Intelligence | cs.AI | In this paper we consider the nature of the machine intelligences we have
created in the context of our human intelligence. We suggest that the
fundamental difference between human and machine intelligence comes down to
\emph{embodiment factors}. We define embodiment factors as the ratio between an
entity's ability to ... | computer science |
20,944 | Logical Learning Through a Hybrid Neural Network with Auxiliary Inputs | cs.AI | The human reasoning process is seldom a one-way process from an input leading
to an output. Instead, it often involves a systematic deduction by ruling out
other possible outcomes as a self-checking mechanism. In this paper, we
describe the design of a hybrid neural network for logical learning that is
similar to the h... | computer science |
20,945 | XOR-Sampling for Network Design with Correlated Stochastic Events | cs.AI | Many network optimization problems can be formulated as stochastic network
design problems in which edges are present or absent stochastically.
Furthermore, protective actions can guarantee that edges will remain present.
We consider the problem of finding the optimal protection strategy under a
budget limit in order t... | computer science |
20,946 | Enhanced Experience Replay Generation for Efficient Reinforcement
Learning | cs.AI | Applying deep reinforcement learning (RL) on real systems suffers from slow
data sampling. We propose an enhanced generative adversarial network (EGAN) to
initialize an RL agent in order to achieve faster learning. The EGAN utilizes
the relation between states and actions to enhance the quality of data samples
generate... | computer science |
20,947 | Explaining Transition Systems through Program Induction | cs.AI | Explaining and reasoning about processes which underlie observed black-box
phenomena enables the discovery of causal mechanisms, derivation of suitable
abstract representations and the formulation of more robust predictions. We
propose to learn high level functional programs in order to represent abstract
models which ... | computer science |
20,948 | Thinking Fast and Slow with Deep Learning and Tree Search | cs.AI | Sequential decision making problems, such as structured prediction, robotic
control, and game playing, require a combination of planning policies and
generalisation of those plans. In this paper, we present Expert Iteration
(ExIt), a novel reinforcement learning algorithm which decomposes the problem
into separate plan... | computer science |
20,949 | Knowledge Acquisition, Representation \& Manipulation in Decision
Support Systems | cs.AI | In this paper we present a methodology and discuss some implementation issues
for a project on statistical/expert approach to data analysis and knowledge
acquisition. We discuss some general assumptions underlying the project.
Further, the requirements for a user-friendly computer assistant are specified
along with the... | computer science |
20,950 | Uplift Modeling with Multiple Treatments and General Response Types | cs.AI | Randomized experiments have been used to assist decision-making in many
areas. They help people select the optimal treatment for the test population
with certain statistical guarantee. However, subjects can show significant
heterogeneity in response to treatments. The problem of customizing treatment
assignment based o... | computer science |
20,951 | Predictive Analytics for Enhancing Travel Time Estimation in Navigation
Apps of Apple, Google, and Microsoft | cs.AI | The explosive growth of the location-enabled devices coupled with the
increasing use of Internet services has led to an increasing awareness of the
importance and usage of geospatial information in many applications. The
navigation apps (often called Maps), use a variety of available data sources to
calculate and predi... | computer science |
20,952 | Efficient, Safe, and Probably Approximately Complete Learning of Action
Models | cs.AI | In this paper we explore the theoretical boundaries of planning in a setting
where no model of the agent's actions is given. Instead of an action model, a
set of successfully executed plans are given and the task is to generate a plan
that is safe, i.e., guaranteed to achieve the goal without failing. To this
end, we s... | computer science |
20,953 | Logic Tensor Networks for Semantic Image Interpretation | cs.AI | Semantic Image Interpretation (SII) is the task of extracting structured
semantic descriptions from images. It is widely agreed that the combined use of
visual data and background knowledge is of great importance for SII. Recently,
Statistical Relational Learning (SRL) approaches have been developed for
reasoning under... | computer science |
20,954 | Cross-Domain Perceptual Reward Functions | cs.AI | In reinforcement learning, we often define goals by specifying rewards within
desirable states. One problem with this approach is that we typically need to
redefine the rewards each time the goal changes, which often requires some
understanding of the solution in the agents environment. When humans are
learning to comp... | computer science |
20,955 | An Empirical Analysis of Approximation Algorithms for the Euclidean
Traveling Salesman Problem | cs.AI | With applications to many disciplines, the traveling salesman problem (TSP)
is a classical computer science optimization problem with applications to
industrial engineering, theoretical computer science, bioinformatics, and
several other disciplines. In recent years, there have been a plethora of novel
approaches for a... | computer science |
20,956 | Finding Robust Solutions to Stable Marriage | cs.AI | We study the notion of robustness in stable matching problems. We first
define robustness by introducing (a,b)-supermatches. An $(a,b)$-supermatch is a
stable matching in which if $a$ pairs break up it is possible to find another
stable matching by changing the partners of those $a$ pairs and at most $b$
other pairs. I... | computer science |
20,957 | Logical and Inequality Implications for Reducing the Size and Complexity
of Quadratic Unconstrained Binary Optimization Problems | cs.AI | The quadratic unconstrained binary optimization (QUBO) problem arises in
diverse optimization applications ranging from Ising spin problems to classical
problems in graph theory and binary discrete optimization. The use of
preprocessing to transform the graph representing the QUBO problem into a
smaller equivalent grap... | computer science |
20,958 | Multi-shot ASP solving with clingo | cs.AI | We introduce a new flexible paradigm of grounding and solving in Answer Set
Programming (ASP), which we refer to as multi-shot ASP solving, and present its
implementation in the ASP system clingo.
Multi-shot ASP solving features grounding and solving processes that deal
with continuously changing logic programs. In d... | computer science |
20,959 | Quadratic Unconstrained Binary Optimization Problem Preprocessing:
Theory and Empirical Analysis | cs.AI | The Quadratic Unconstrained Binary Optimization problem (QUBO) has become a
unifying model for representing a wide range of combinatorial optimization
problems, and for linking a variety of disciplines that face these problems. A
new class of quantum annealing computer that maps QUBO onto a physical qubit
network struc... | computer science |
20,960 | Inexpensive Cost-Optimized Measurement Proposal for Sequential
Model-Based Diagnosis | cs.AI | In this work we present strategies for (optimal) measurement selection in
model-based sequential diagnosis. In particular, assuming a set of leading
diagnoses being given, we show how queries (sets of measurements) can be
computed and optimized along two dimensions: expected number of queries and
cost per query. By mea... | computer science |
20,961 | Probabilistic Program Abstractions | cs.AI | Abstraction is a fundamental tool for reasoning about complex systems.
Program abstraction has been utilized to great effect for analyzing
deterministic programs. At the heart of program abstraction is the relationship
between a concrete program, which is difficult to analyze, and an abstract
program, which is more tra... | computer science |
20,962 | Should Robots be Obedient? | cs.AI | Intuitively, obedience -- following the order that a human gives -- seems
like a good property for a robot to have. But, we humans are not perfect and we
may give orders that are not best aligned to our preferences. We show that when
a human is not perfectly rational then a robot that tries to infer and act
according t... | computer science |
20,963 | Abstract Argumentation / Persuasion / Dynamics | cs.AI | The act of persuasion, a key component in rhetoric argumentation, may be
viewed as a dynamics modifier. Such modifiers are well-known in other research
fields: recall dynamic epistemic logic where operators modify possible world
accessibilities, or recall side effects and concurrency in programming
languages. We consid... | computer science |
20,964 | Machine Learned Learning Machines | cs.AI | There are two common approaches for optimizing the performance of a machine:
genetic algorithms and machine learning. A genetic algorithm is applied over
many generations whereas machine learning works by applying feedback until the
system meets a performance threshold. Though these are methods that typically
operate s... | computer science |
20,965 | Black-box Testing of First-Order Logic Ontologies Using WordNet | cs.AI | Artificial Intelligence aims to provide computer programs with commonsense
knowledge to reason about our world. This paper offers a new practical approach
towards automated commonsense reasoning with first-order logic (FOL)
ontologies. We propose a new black-box testing methodology of FOL SUMO-based
ontologies by explo... | computer science |
20,966 | Automatic White-Box Testing of First-Order Logic Ontologies | cs.AI | A long-standing dream of Artificial Intelligence (AI) has pursued to encode
commonsense knowledge into computer programs enabling machines to reason about
our world and problems. This work offers a new practical insight towards the
automatic testing of first-order logic (FOL) ontologies. We introduce a novel
fully auto... | computer science |
20,967 | Learning Belief Network Structure From Data under Causal Insufficiency | cs.AI | Though a belief network (a representation of the joint probability
distribution, see [3]) and a causal network (a representation of causal
relationships [14]) are intended to mean different things, they are closely
related. Both assume an underlying dag (directed acyclic graph) structure of
relations among variables an... | computer science |
20,968 | MOBA: a New Arena for Game AI | cs.AI | Games have always been popular testbeds for Artificial Intelligence (AI). In
the last decade, we have seen the rise of the Multiple Online Battle Arena
(MOBA) games, which are the most played games nowadays. In spite of this, there
are few works that explore MOBA as a testbed for AI Research. In this paper we
present a... | computer science |
20,969 | Universal Reinforcement Learning Algorithms: Survey and Experiments | cs.AI | Many state-of-the-art reinforcement learning (RL) algorithms typically assume
that the environment is an ergodic Markov Decision Process (MDP). In contrast,
the field of universal reinforcement learning (URL) is concerned with
algorithms that make as few assumptions as possible about the environment. The
universal Baye... | computer science |
20,970 | Low Impact Artificial Intelligences | cs.AI | There are many goals for an AI that could become dangerous if the AI becomes
superintelligent or otherwise powerful. Much work on the AI control problem has
been focused on constructing AI goals that are safe even for such AIs. This
paper looks at an alternative approach: defining a general concept of `low
impact'. The... | computer science |
20,971 | Strength Factors: An Uncertainty System for a Quantified Modal Logic | cs.AI | We present a new system S for handling uncertainty in a quantified modal
logic (first-order modal logic). The system is based on both probability theory
and proof theory. The system is derived from Chisholm's epistemology. We
concretize Chisholm's system by grounding his undefined and primitive (i.e.
foundational) conc... | computer science |
20,972 | Experience Replay Using Transition Sequences | cs.AI | Experience replay is one of the most commonly used approaches to improve the
sample efficiency of reinforcement learning algorithms. In this work, we
propose an approach to select and replay sequences of transitions in order to
accelerate the learning of a reinforcement learning agent in an off-policy
setting. In addit... | computer science |
20,973 | Towards Learned Clauses Database Reduction Strategies Based on Dominance
Relationship | cs.AI | Clause Learning is one of the most important components of a conflict driven
clause learning (CDCL) SAT solver that is effective on industrial instances.
Since the number of learned clauses is proved to be exponential in the worse
case, it is necessary to identify the most relevant clauses to maintain and
delete the ir... | computer science |
20,974 | Propositional Knowledge Representation in Restricted Boltzmann Machines | cs.AI | Representing symbolic knowledge into a connectionist network is the key
element for the integration of scalable learning and sound reasoning. Most of
the previous studies focus on discriminative neural networks which
unnecessarily require a separation of input/output variables. Recent
development of generative neural n... | computer science |
20,975 | The Atari Grand Challenge Dataset | cs.AI | Recent progress in Reinforcement Learning (RL), fueled by its combination,
with Deep Learning has enabled impressive results in learning to interact with
complex virtual environments, yet real-world applications of RL are still
scarce. A key limitation is data efficiency, with current state-of-the-art
approaches requir... | computer science |
20,976 | A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic
Problems Leveraging the Graphics Processor Unit | cs.AI | Multi-start algorithms are a common and effective tool for metaheuristic
searches. In this paper we amplify multi-start capabilities by employing the
parallel processing power of the graphics processer unit (GPU) to quickly
generate a diverse starting set of solutions for the Unconstrained Binary
Quadratic Optimization... | computer science |
20,977 | Descriptions of Objectives and Processes of Mechanical Learning | cs.AI | In [1], we introduced mechanical learning and proposed 2 approaches to
mechanical learning. Here, we follow one such approach to well describe the
objects and the processes of learning. We discuss 2 kinds of patterns:
objective and subjective pattern. Subjective pattern is crucial for learning
machine. We prove that fo... | computer science |
20,978 | Diversified Top-k Partial MaxSAT Solving | cs.AI | We introduce a diversified top-k partial MaxSAT problem, a combination of
partial MaxSAT problem and enumeration problem. Given a partial MaxSAT formula
F and a positive integer k, the diversified top-k partial MaxSAT is to find k
maximal solutions for F such that the k maximal solutions satisfy the maximum
number of s... | computer science |
20,979 | Grounding Symbols in Multi-Modal Instructions | cs.AI | As robots begin to cohabit with humans in semi-structured environments, the
need arises to understand instructions involving rich variability---for
instance, learning to ground symbols in the physical world. Realistically, this
task must cope with small datasets consisting of a particular users' contextual
assignment o... | computer science |
20,980 | Enhancing workflow-nets with data for trace completion | cs.AI | The growing adoption of IT-systems for modeling and executing (business)
processes or services has thrust the scientific investigation towards
techniques and tools which support more complex forms of process analysis. Many
of them, such as conformance checking, process alignment, mining and
enhancement, rely on complet... | computer science |
20,981 | Modeling Latent Attention Within Neural Networks | cs.AI | Deep neural networks are able to solve tasks across a variety of domains and
modalities of data. Despite many empirical successes, we lack the ability to
clearly understand and interpret the learned internal mechanisms that
contribute to such effective behaviors or, more critically, failure modes. In
this work, we pres... | computer science |
20,982 | Exception-Based Knowledge Updates | cs.AI | Existing methods for dealing with knowledge updates differ greatly depending
on the underlying knowledge representation formalism. When Classical Logic is
used, updates are typically performed by manipulating the knowledge base on the
model-theoretic level. On the opposite side of the spectrum stand the semantics
for u... | computer science |
20,983 | Joint Matrix-Tensor Factorization for Knowledge Base Inference | cs.AI | While several matrix factorization (MF) and tensor factorization (TF) models
have been proposed for knowledge base (KB) inference, they have rarely been
compared across various datasets. Is there a single model that performs well
across datasets? If not, what characteristics of a dataset determine the
performance of MF... | computer science |
20,984 | ICABiDAS: Intuition Centred Architecture for Big Data Analysis and
Synthesis | cs.AI | Humans are expert in the amount of sensory data they deal with each moment.
Human brain not only analyses these data but also starts synthesizing new
information from the existing data. The current age Big-data systems are needed
not just to analyze data but also to come up new interpretation. We believe
that the pivot... | computer science |
20,985 | Actor-Critic for Linearly-Solvable Continuous MDP with Partially Known
Dynamics | cs.AI | In many robotic applications, some aspects of the system dynamics can be
modeled accurately while others are difficult to obtain or model. We present a
novel reinforcement learning (RL) method for continuous state and action spaces
that learns with partial knowledge of the system and without active
exploration. It solv... | computer science |
20,986 | 3D Pathfinding and Collision Avoidance Using Uneven Search-space
Quantization and Visual Cone Search | cs.AI | Pathfinding is a very popular area in computer game development. While
two-dimensional (2D) pathfinding is widely applied in most of the popular game
engines, little implementation of real three-dimensional (3D) pathfinding can
be found. This research presents a dynamic search space optimization algorithm
which can be ... | computer science |
20,987 | A method for the online construction of the set of states of a Markov
Decision Process using Answer Set Programming | cs.AI | Non-stationary domains, that change in unpredicted ways, are a challenge for
agents searching for optimal policies in sequential decision-making problems.
This paper presents a combination of Markov Decision Processes (MDP) with
Answer Set Programming (ASP), named {\em Online ASP for MDP} (oASP(MDP)), which
is a method... | computer science |
20,988 | Unsupervised Neural-Symbolic Integration | cs.AI | Symbolic has been long considered as a language of human intelligence while
neural networks have advantages of robust computation and dealing with noisy
data. The integration of neural-symbolic can offer better learning and
reasoning while providing a means for interpretability through the
representation of symbolic kn... | computer science |
20,989 | Epistemic Logic with Functional Dependency Operator | cs.AI | Epistemic logic with non-standard knowledge operators, especially the
"knowing-value" operator, has recently gathered much attention. With the
"knowing-value" operator, we can express knowledge of individual variables, but
not of the relations between them in general. In this paper, we propose a new
operator Kf to expr... | computer science |
20,990 | Regular Boardgames | cs.AI | We present an initial version of Regular Boardgames general game description
language. This stands as an extension of Simplified Boardgames language. Our
language is designed to be able to express the rules of a majority of popular
boardgames including the complex rules such as promotions, castling, en
passant, jump ca... | computer science |
20,991 | Responsible Autonomy | cs.AI | As intelligent systems are increasingly making decisions that directly affect
society, perhaps the most important upcoming research direction in AI is to
rethink the ethical implications of their actions. Means are needed to
integrate moral, societal and legal values with technological developments in
AI, both during t... | computer science |
20,992 | What Does a Belief Function Believe In ? | cs.AI | The conditioning in the Dempster-Shafer Theory of Evidence has been defined
(by Shafer \cite{Shafer:90} as combination of a belief function and of an
"event" via Dempster rule.
On the other hand Shafer \cite{Shafer:90} gives a "probabilistic"
interpretation of a belief function (hence indirectly its derivation from a... | computer science |
20,993 | On the Development of Intelligent Agents for MOBA Games | cs.AI | Multiplayer Online Battle Arena (MOBA) is one of the most played game genres
nowadays. With the increasing growth of this genre, it becomes necessary to
develop effective intelligent agents to play alongside or against human
players. In this paper we address the problem of agent development for MOBA
games. We implement... | computer science |
20,994 | The FastMap Algorithm for Shortest Path Computations | cs.AI | We present a new preprocessing algorithm for embedding the nodes of a given
edge-weighted undirected graph into a Euclidean space. The Euclidean distance
between any two nodes in this space approximates the length of the shortest
path between them in the given graph. Later, at runtime, a shortest path
between any two n... | computer science |
20,995 | Rapid Randomized Restarts for Multi-Agent Path Finding Solvers | cs.AI | Multi-Agent Path Finding (MAPF) is an NP-hard problem well studied in
artificial intelligence and robotics. It has many real-world applications for
which existing MAPF solvers use various heuristics. However, these solvers are
deterministic and perform poorly on "hard" instances typically characterized by
many agents i... | computer science |
20,996 | Bandit Models of Human Behavior: Reward Processing in Mental Disorders | cs.AI | Drawing an inspiration from behavioral studies of human decision making, we
propose here a general parametric framework for multi-armed bandit problem,
which extends the standard Thompson Sampling approach to incorporate reward
processing biases associated with several neurological and psychiatric
conditions, including... | computer science |
20,997 | Evidence Against Evidence Theory (?!) | cs.AI | This paper is concerned with the apparent greatest weakness of the
Mathematical Theory of Evidence (MTE) of Shafer \cite{Shafer:76}, which has
been strongly criticized by Wasserman \cite{Wasserman:92ijar} - the
relationship to frequencies.
Weaknesses of various proposals of probabilistic interpretation of MTE belief
... | computer science |
20,998 | Off The Beaten Lane: AI Challenges In MOBAs Beyond Player Control | cs.AI | MOBAs represent a huge segment of online gaming and are growing as both an
eSport and a casual genre. The natural starting point for AI researchers
interested in MOBAs is to develop an AI to play the game better than a human -
but MOBAs have many more challenges besides adversarial AI. In this paper we
introduce the re... | computer science |
20,999 | A Focal Any-Angle Path-finding Algorithm Based on A* on Visibility
Graphs | cs.AI | In this research, we investigate the subject of path-finding. A pruned
version of visibility graph based on Candidate Vertices is formulated, followed
by a new visibility check technique. Such combination enables us to quickly
identify the useful vertices and thus find the optimal path more efficiently.
The algorithm p... | computer science |
21,000 | Deep Optimization for Spectrum Repacking | cs.AI | Over 13 months in 2016-17 the FCC conducted an "incentive auction" to
repurpose radio spectrum from broadcast television to wireless internet. In the
end, the auction yielded $19.8 billion, $10.05 billion of which was paid to 175
broadcasters for voluntarily relinquishing their licenses across 14 UHF
channels. Stations... | computer science |
21,001 | Data-Efficient Policy Evaluation Through Behavior Policy Search | cs.AI | We consider the task of evaluating a policy for a Markov decision process
(MDP). The standard unbiased technique for evaluating a policy is to deploy the
policy and observe its performance. We show that the data collected from
deploying a different policy, commonly called the behavior policy, can be used
to produce unb... | computer science |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.